What on earth do you mean by CONTEXT ?

I have to thank Frank Scavo for making me think harder about what context means . I and several people I know use the term liberally , and perhaps not very consistently .

Here is my hypothesis –

Answer to every question has a core (which has great precision) and a context (less precise , but without it -core cannot be meaningfully interpreted).

1. Additional questions maybe needed to get context

If all I ask you on phone is “should I turn right or left to reach your office” , you probably will ask me something in return like “are you coming from north or south”. Without this additional information, you cannot help me . Right or left is a precise answer , what is on my right might be on your left or right . Without extra information – you cannot help me with a precise answer .

2. You can infer all or part of the context from historical information .

Maybe you know from your morning commute that I could never be driving from south side on that street given that side of road is blocked for construction . So you can give me a precise left or right answer without asking me anything further.

3. Context can change with time

Perhaps turning right will be the shortest distance to your office , yet you might ask me to turn left since you know rush hour traffic going on now will slow me down . If I had asked you two hours later – you could have given me the exact opposite answer , and still be correct .

4. Multiple things together might be needed to provide context

It is very seldom that one extra bit of information is all you need to make a determination . When I called you during rush hour , if it was raining – you might have asked me to take a left turn so that I will get covered parking and a shuttle to ride to your office . On a sunny day, you could have pointed me to an open lot from where I could have walked a short distance to reach you .

5. Context is progressively determined

As the number of influencing factors increase – you have to determine trade offs progressively to arrive at a useful context . You might know exactly all the right questions to ask to give me the best answer , but if you were pressed for time – you could have told me an answer without considering the entire context . It would have been precise, but probably of limited use to me .

6. Context is user dependent

If I reached your assistant instead of you , she probably would need a whole different context to be provided before she could tell me which way to turn . She might have never taken the route you take to work , and hence might not have seen southbound traffic is closed off . She might not have realized it is raining outside given she was in meetings all day .

If I am your vendor and you know I am coming there to make a pitch that you have limited interest in – you probably won’t think through all the contextual information . If I am your customer – maybe you will go outbid your way to tell me not just to turn right , but also that the particular turn comes 100 yards from the big grocery store I will find on my right .

7. More information does not always lead to better context

If I over loaded you with information – you probably could not have figured out all the trade offs in the few seconds you have before responding . Your best answer might not be optimal . And if you take very long to respond , I might pass the place to make the turn and then have to track back – making it needlessly harder for both of us .

8. Context maybe more useful that precision

Instead of giving me a precise left or right answer , you might tell me to park in front of the big train station and wait for your company shuttle to pick me up. That was not the precise answer to my question – but it still was more useful to me .

This was just a simple question with only two possibilities as precise answers . Think of a question in a business scenario . “How are our top customers doing?” is a common question that you can hear at a company . However , you can’t answer that question in any meaningful way without plenty of context .

The eventual precise answer is “good” or “bad”. What makes the question difficult is that it could mean a lot of different things .
1. What is a top customer ? Most volume ? Most sales ? Most profit ? Longest history with company ? Most visible in industry ? Most market cap?
2. Who is asking ? CMO and CFO might not have the same idea on what makes a top customer
3. How many should you consider as top customers amongst all your customers ?
And so on ..

Information systems in majority of companies do not have the ability to collect context of a question . And hence they may or may not give useful answers without a human user doing most of the thinking and combining various “precise” answers to find out a “useful” answer .

That is a long winded way of saying “context is what makes precision useful”.

Ok I am done – let me know if this makes any sense at all , and more importantly whether it resonates with your idea of what context means

Published by Vijay Vijayasankar

Son/Husband/Dad/Dog Lover/Engineer. Follow me on twitter @vijayasankarv. These blogs are all my personal views - and not in way related to my employer or past employers

7 thoughts on “What on earth do you mean by CONTEXT ?

  1. Vijay – this context post was thought-provoking…going with your driving analogy, as you know what I am most interested in is the impact not necessarily of big data but smart real-time data from external data sources that can affect decisions. So in the driving case, let’s say we are on the phone and you are giving me directions to a really good restaurant with food that is too spicy for me but just right for you (lol). You recommend an expressway that is the best route at that time of day (a personalized context).

    Only in this case, the context is flawed because you don’t know about a traffic accident that just happened on that expressway. However, my GPS has a crowd-sourced feed that quickly alerts me to the pending traffic problem before I get stuck in it. I take an exit and you then guide me to a better course based on that new information.

    Of course, there are a couple of problems here for the enterprise application of this example: when you go from one-to-one to many-to-many, it’s much harder to scale the real-time info and get it to the person most impacted. Second, even if you managed to do that, typically in an enterprise situation there isn’t one obvious answer (take the route without the care pileup) – usually there are multiple options, each with tradeoffs (this warehouse has the parts we need, but it’s a shipping delay to the customer, this closer warehouse has the part but in less quantity than the customer needs, etc).

    Then, even if you make the right decision with those tradeoffs taken into account, your best case scenario is saving money, efficiency, time – which is very good. But it’s not the same as using that new data to build new markets and seize new sales opportunities. Of course, if you figure out what those new opportunities are (e.g. we should overstock on certain items when weather patterns change), once that “business rule” is established some of the growth/top line opportunities can be automated or at least established under business conditions that make sense to the person authorizing. But someone who knows how to build new markets and take the appropriate risks to do so has to establish that business rule first based on analyzing the context and real-time feed potential, etc.

    Thanks for advancing the discussion, curious to hear your comments. 🙂


  2. As always your articles spur great thoughts and conversations. I have shared this with those within my brain-trust and it has created great discussions.


  3. Hey Vijay,

    Here’s how I think about it — an inference is a function of an answer and it’s context.

    This context in itself is a function of several factors, many of which you mention above — who, where, when, history etc. of both the question and the answer. But also the the who, when, where, history, reliability etc. of each factor in itself. The programmer in me is thinking recursive inquiry into each influencing factor of each factor, of each factor and so forth.

    If the above is true, determining absolute context is very hard or time consuming, so I prefer to think of context in terms of its resolution (like in pictures), a high resolution context results in a high resolution inference.

    However, determining the right resolution of context needed to reach a satisfactory resolution of inference is quite difficult. A magic trick for example is all about revealing only a part of the context to create an illusion masquerading as an inference.

    In business, we need be careful not to fall for these illusions.



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